Abstract
Music consumption is shaped by both internal factors (e.g., mood, motivation) and external factors (e.g., activity, social environment), which together influence listeners’ behavior (e.g., focus, songs’ skips) and reactions (e.g., mood changes). While prior research has explored real-life or survey-based, context-aware music listening with limited available context information, we introduce a dataset comprising 216 music listening sessions collected in real-world settings through a custom-built Android mobile application designed to assess a wide range of contextual factors. The dataset captures static (e.g., activity, social environment, motivation) and dynamic (e.g., mood changes) contextual factors, along with music interaction data (e.g., skipped or fully listened songs), listening focus levels, and participant traits (e.g., demographics, music education, listening preferences, personality). Our analysis highlights key insights into how different contextual factors influence user behavior and mood. demonstrating significant differences in skipping songs, focus levels, and genre diversity. We show that music listening sessions grouped by context are significantly different in terms of music listening behaviors (focus, skipping, and session genre diversity) and mood changes (happiness, sadness, stress, and energy). Furthermore, we explore the correlations between personality traits and listening behaviors (mean skip rate and genre diversity). Ultimately, our findings emphasize the importance of understanding context, as different situations lead to distinct music preferences and have varying impacts on user behavior and emotional responses.
Citation
Anna
Hausberger,
Emilia Parada-Cabaleiro,
Markus
Schedl
Why Context Matters: Exploring How Musical Context Impacts User Behavior, Mood, and Musical Preferences
Proceedings of the 33nd ACM Conference on User Modeling, Adaptation and Personalization (UMAP), doi:10.1145/3699682.3728354, 2025.
BibTeX
@inproceedings{Hausberger2025context,
title = {Why Context Matters: Exploring How Musical Context Impacts User Behavior, Mood, and Musical Preferences},
author = {Hausberger, Anna and Emilia Parada-Cabaleiro and Schedl, Markus},
booktitle = {Proceedings of the 33nd ACM Conference on User Modeling, Adaptation and Personalization (UMAP)},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
doi = {10.1145/3699682.3728354},
year = {2025}
}